CompatHelper: bump compat for Setfield to 0.8 for package test, (keep existing compat) #33
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This is a draft PR introducing a `Model` type that stores and makes use the model graph.
The main type introduced here is the `Model` struct which stores the `ModelState` and `DAG`, each of which are their own types. `ModelState` contains information about the node values, dependencies and eval functions and `DAG` contains the graph and topologically ordered vertex list.
A model can be constructed in the following way:
```julia
julia> nt = (
s2 = (0.0, (), () -> InverseGamma(2.0,3.0), :Stochastic),
μ = (1.0, (), () -> 1.0, :Logical),
y = (0.0, (:μ, :s2), (μ, s2) -> MvNormal(μ, sqrt(s2)), :Stochastic)
)
(s2 = (0.0, (), var"#33#36"(), :Stochastic), μ = (1.0, (), var"#34#37"(), :Logical), y = (0.0, (:μ, :s2), var"#35#38"(), :Stochastic))
julia> Model(nt)
Nodes:
μ = (value = 1.0, input = (), eval = var"#16#19"(), kind = :Logical)
s2 = (value = 0.0, input = (), eval = var"#15#18"(), kind = :Stochastic)
y = (value = 0.0, input = (:μ, :s2), eval = var"#17#20"(), kind = :Stochastic)
DAG:
3×3 SparseMatrixCSC{Float64, Int64} with 2 stored entries:
⋅ ⋅ ⋅
⋅ ⋅ ⋅
1.0 1.0 ⋅
```
At present, only functions needed for the constructors are implemented, as well as indexing using `@varname`. I still need to complete the integration with the AbstractPPL api. TODO:
~~- [ ] `condition`/`decondition`,~~
~~- [ ] `sample`~~
~~- [ ] `logdensityof`~~
- [x] pure functions for ordered dictionary, as outlined in [AbstractPPL](https://github.com/TuringLang/AbstractPPL.jl#property-interface)
Feedback on `Model` structure welcome whilst I implement the remaining features!
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This pull request changes the compat entry for the
Setfieldpackage from0.7.1to0.7.1, 0.8for package test.This keeps the compat entries for earlier versions.
Note: I have not tested your package with this new compat entry.
It is your responsibility to make sure that your package tests pass before you merge this pull request.